Since our TSR can output a \(256\times 256\)  probability map for edge and line respectively; of course, we can directly use this probability map as the repair result of our edge and line. However, we find that the recall is still insufficient.
Fig. REF (b)(c) show that it can only predict a few regions with high confidence. But the probability confidence for the inner masked region is low, which leads to incomplete structures. As a result, we employ the Mask-Predict  [1]}, [2]}, [3]} strategy. It predicts all target pixels at the first iteration. Then we re-mask and re-predict pixels with low-confidence iteratively for a constant number of iterations. Note that we just re-mask edge and line without re-masking the input masked image. This technique can achieve more complete structural information as illustrated in Fig. REF (d)(e). We set the total number of iterations to 5 in our experiment for a trade-off between inference time and recall. Fig. REF  shows our outcomes with different Mask-Predict iterations. Note that we ignore pixels with low confidence for each iteration in Fig. REF , so the iteration 1 results of Fig. REF (c) look different from the results without Mask-Predict.
The inside portion of the mask can be gradually restored with larger iterations as shown in Fig. REF .
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